Field
Various communication systems may benefit from physical layer watermarking. For example, active sensing for dynamic spectrum access may be performed using physical layer watermarking, such as watermarking based on channel effects and/or receiver distortion.
Description of the Related Art
As wireless communication has become a ubiquitous part of every-day life, access to the electromagnetic spectrum has become increasingly competitive. To facilitate efficient use of limited spectral resources, an arbitration method known as Dynamic Spectrum Access (DSA) has been proposed. Wireless Regional Area Networks (WRAN), for example as standardized at Institute of Electrical and Electronics Engineers (IEEE) 802.22, may also include spectrum sensing and shared spectrum technologies. Under IEEE 802.22, limited access to the unused spectrum between Digital Television (DTV) channels, or the white space spectrum, is granted to next-generation wireless broadband equipment. In particular, licensed DTV stations, or primary users, are given explicit first-right-of-access to television spectrum, while broadband users known as secondary users, are allowed access to the shared spectrum only when a primary user is not transmitting. While DSA shows promise in facilitating efficient spectrum access, accurate signal classification may be required to facilitate the robust operation of next-generation wireless radios and the interoperability of DSA equipment.
To ensure efficient use of white space spectrum under IEEE 802.22, spectral allocations can first be tested to guarantee that primary users are not present before secondary users are granted access to an allocation. Since the accurate detection of primary users may be required for correct utilization of the shared spectrum, this issue has become known as the Primary User Authentication (PUA) problem.
Traditional approaches to signal identification involving the computation of statistical properties or cyclostationary features have been proposed. These approaches can be referred to as passive signal characterization methods since the transmitter does not explicitly participate in the detection and classification process, nor does it modify characteristics of its signal to aid the detection and classification process. Classification approaches using these features in DSA scenarios have also been discussed, including machine learning and policy-based classification engines. These works have demonstrated the utility of machine learning approaches in signal classification applications. However, in non-cooperative environments, adversaries can easily manipulate the learning process by fooling passive signal characterization methods, exposing DSA systems to a number of identity-based attacks.
While passive approaches readily admit to low complexity implementations, secondary users may masquerade as primary users by simply mimicking basic features of a primary users' signal. Once a secondary user has been incorrectly classified as a primary user, the user can gain unfettered access to the spectrum. These attacks have become known as Primary User Emulation (PUE) attacks.